以下是quickselect的代码
def quickSelect(lst, k):
if len(lst) != 0:
pivot = lst[(len(lst)) // 2]
smallerList = []
for i in lst:
if i < pivot:
smallerList.append(i)
largerList = []
for i in lst:
if i > pivot:
largerList.append(i)
count = len(lst) - len(smallerList) - len(largerList)
m = len(smallerList)
if k >= m and k < m + count:
return pivot
print(pivot)
elif m > k:
return quickSelect(smallerList, k)
else:
return quickSelect(largerList, k-m-count)
我遇到的问题是它运行时没有任何错误或任何东西,但是当它完成时我希望它输出一些东西到python shell(在这个特定情况下是列表的中间值),但我什么都没有回来。我在这里做错了吗?
至于我为lst和k输入的内容......
我尝试了几个不同的k值,但无济于事
答案 0 :(得分:3)
您可以使用列表推导来优化此算法。另外,我认为你不需要数......
def quickSelect(seq, k):
# this part is the same as quick sort
len_seq = len(seq)
if len_seq < 2: return seq
ipivot = len_seq // 2
pivot = seq[ipivot]
smallerList = [x for i,x in enumerate(seq) if x <= pivot and i != ipivot]
largerList = [x for i,x in enumerate(seq) if x > pivot and i != ipivot]
# here starts the different part
m = len(smallerList)
if k == m:
return pivot
elif k < m:
return quickSelect(smallerList, k)
else:
return quickSelect(largerList, k-m-1)
if __name__ == '__main__':
# Checking the Answer
seq = [10, 60, 100, 50, 60, 75, 31, 50, 30, 20, 120, 170, 200]
# we want the middle element
k = len(seq) // 2
# Note that this only work for odd arrays, since median in
# even arrays is the mean of the two middle elements
print(quickSelect(seq, k))
import numpy
print numpy.median(seq)
答案 1 :(得分:0)
def quickSelect(lst, k):
if len(lst) != 0:
pivot = lst[(len(lst)) // 2]
smallerList = []
for i in lst:
if i < pivot:
smallerList.append(i)
largerList = []
for i in lst:
if i > pivot:
largerList.append(i)
count = len(lst) - len(smallerList) - len(largerList)
m = len(smallerList)
if k >= m and k < m + count:
return pivot
print(pivot)
elif m > k:
return quickSelect(smallerList, k)
else:
return quickSelect(largerList, k-m-count)
lst = [70, 120, 170, 200]
k = len(lst) // 2
print(quickSelect(lst, k))
产生
>>> 170
我唯一纠正的是缩进。